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Synthetic example data

This directory contains a deterministic, self-contained dataset for the KLRfome README workflow and automated smoke tests.

Files

  • var1.tif, var2.tif, and var3.tif: three aligned 200 × 200 environmental rasters;
  • sites.geojson: 25 simulated site points; and
  • metadata.json: generation settings, extent, CRS, and random seed.

The rasters contain spatially autocorrelated synthetic variables. Site locations were generated with a learnable environmental association. The data demonstrate software behavior only and are not evidence for selecting among M0–M3.

Run the CI-sized end-to-end workflow from the repository root:

python examples/readme_quickstart.py

Run focal prediction over the complete example extent with:

python examples/readme_quickstart.py --full-surface

The fitted example is a presence-background design, so its output is a relative-suitability surface rather than an occurrence-probability surface. See the main README and model/data foundation for the current API and interpretation.